Automated image analysis
Research type
Research Study
Full title
Automated image analysis in retinal diseases
IRAS ID
232305
Contact name
Mital Shah
Contact email
Sponsor organisation
Oxford University Hospitals NHS Foundation Trust
Duration of Study in the UK
2 years, 0 months, 1 days
Research summary
Clinical data, such as from retinal imaging, contains a wealth of information. However, its analysis is currently limited by manual techniques. In this study, we will use existing clinical data of patients with retinal diseases to explore a novel methodology for the automated analysis of retinal images. The anonymised clinical data will include information from clinical imaging and functional studies and health records. This novel approach to the analysis of clinical data has already shown some promising results in the detection of diabetic retinopathy from colour retinal photographs and other work in this area is ongoing. Existing algorithms that utilise automated techniques traditionally have very large datasets available with which to develop the algorithms. While this technique is feasible in applications such as data security, access to such large datasets in a real world healthcare setting are impractical. In this study, in addition to utilising the novel methodology of automated image analysis, we will also implement this technique using a much smaller dataset than traditionally used.
REC name
London - West London & GTAC Research Ethics Committee
REC reference
17/LO/1604
Date of REC Opinion
18 Sep 2017
REC opinion
Unfavourable Opinion